Biology subjects

Qiu, W.

Publications and source records attributed to Qiu, W..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

Hepatic Deletion of X-box Binding Protein 1 in Farnesoid X Receptor Null Mice Leads to Enhanced Liver Injury

Background & AimsFarnesoid X receptor (FXR) regulates bile acid metabolism and FXR null (Fxr-/-) mice have elevated bile acid levels and progressive liver injury. The inositol-requiring enzyme 1 (IRE1)/X-box binding protein 1 (XBP1) pathway is a protective pathway of the unfolded protein response (UPR) that is activated in response to ER stress. In this study we sought to determine the role of the UPR in Fxr-/- mice. Approach & ResultsWe examined hepatic UPR gene and protein expression in 10- and 24-week-old wild type (WT) and Fxr-/- mice. Hepatic XBP1 and other UPR pathways were activated in 24-week-old Fxr-/- mice, but not WT mice. To further determine the role of the liver UPR activation in Fxr-/- mice, we generated mice with FXR and liver-specific XBP1 double knockout (DKO, Fxr-/-Xbp1LKO) and Fxr-/- Xbp1fl/fl single knockout (SKO) mice and characterized their phenotypes at different ages. DKO mice demonstrated enhanced liver injury, apoptosis and fibrosis compared with SKO mice. RNA-seq revealed increased gene expression in apoptosis, inflammation and cell proliferation pathways in DKO mice. The proapoptotic C/EBP-homologous protein (CHOP) pathway was activated in DKO mice. At age 60 weeks, all DKO mice and no SKO mice spontaneously developed liver tumors. ConclusionsThe hepatic XBP1 pathway is activated in older Fxr-/- mice and has a protective role. The potential interaction between XBP1 and FXR signaling may be important in modulating the hepatocellular cholestatic stress responses.

molecular biology↗

bioRxiv2022

Cholesterol in the cargo membrane reduces kinesin-1 binding to microtubules in the presence of tau

Intracellular cargos are often membrane-bound and transported by microtubule-based motors in the presence of microtubule-associated proteins (MAPs). Whereas increasing evidence reveals how MAPs impact the interactions between motors and microtubules, critical questions remain about the impact of the cargo membrane on transport. Here we combined in vitro optical trapping with theoretical approaches to determine the effect of a lipid cargo membrane on kinesin-based transport in the presence of MAP tau. Attaching kinesins to a fluid lipid membrane decreases the inhibitory effect of tau in comparison to membrane-free cargos. Adding cholesterol, which reduces kinesin diffusion in the cargo membrane, amplifies the inhibitory effect of tau on kinesin in a dosage-dependent manner. Our findings can be understood in a framework in which kinesin diffusion in the cargo membrane counteracts binding-site occlusion by tau. Our study establishes a direct link between the physical properties of cargo membrane and MAP-based regulation of kinesin-1.

biophysics↗

bioRxiv2022

A Model-Based Clustering via Mixture of Bayesian Hierarchical Models with Covariate Adjustment for Detecting Differentially Expressed Genes from Paired Design

The causes of many complex human diseases are still largely unknown. Genetics plays an important role in uncovering the molecular mechanisms of complex human diseases. A key step to characterize the genetics of a complex human disease is to unbiasedly identify disease-associated gene transcripts in whole-genome scale. Confounding factors could cause false positives. Paired design, such as measuring gene expression before and after treatment for the same subject, can reduce the effect of known confounding factors. Model-based clustering, such as mixtures of Bayesian hierarchical models, has been proposed to detect gene transcripts differentially expressed between paired samples. However, not all known confounding factors can be controlled in a paired/match design. To the best of our knowledge, no clustering methods have the capacity to adjust for the effects of covariates yet. In this article, we proposed a novel mixture of Bayesian hierarchical models with covariate adjustment in identifying differentially expressed transcripts using high-throughput whole-genome data from paired design. Both simulation study and real data analysis show the good performance of the proposed method

genomics↗

bioRxiv2022

CRISPR-based targeted haplotype-resolved assemblies of a megabase region

Constructing high-quality haplotype-resolved genome assemblies has substantially improved the ability to detect and characterize genetic variants. A targeted approach providing readily access to the rich information from haplotype-resolved genome assemblies will be appealing to groups of basic researchers and medical scientists focused on specific genomic regions. Here, using the 4.5 megabase, notoriously difficult-to-assemble major histocompatibility complex (MHC) region as an example, we demonstrated an approach to construct haplotype-resolved de novo assemblies of targeted genomic regions with the CRISPR-based enrichment. Compared to the results from haplotype-resolved genome assemblies, our targeted approach achieved comparable completeness and accuracy with greatly reduced computing complexity, sequencing cost, as well as the amount of starting materials. Moreover, using the targeted assembled personal haplotypes as the reference both improves the quantification accuracy for sequencing data and enables allele-specific functional genomics analyses. Given its highly efficient use of resources, our approach can greatly facilitate population genetic studies of targeted regions, and may pave a new way to elucidate the molecular mechanisms in disease etiology.

genomics↗

bioRxiv2021

Influence of sequencing depth on the fidelity and sensitivity of 1%-5% low-frequency mutation detection and recommendation for standardization of sequencing depth

Sequencing depth has always played an important role in the accurate detection of low-frequency mutations. The increase of sequencing depth and the reasonable setting of threshold can maximize the probability of true positive mutation, or sensitivity. Here, we found that when the threshold was set as a fixed number of positive mutated reads, the probability of both true and false-positive mutations increased with depth. However, When the number of positive mutated reads increased in an equal proportion with depth (the threshold was transformed from a fixed number to a fixed percentage of mutated reads), the true positive probability still increased while false positive probability decreased. Through binomial distribution simulation and experimental test, it is found that the "fidelity" of detected-VAFs is the cause of this phenomenon. Firstly, we used the binomial distribution to construct a model that can easily calculate the relationship between sequencing depth and probability of true positive (or false positive), which can standardize the minimum sequencing depth for different low-frequency mutation detection. Then, the effect of sequencing depth on the fidelity of NA12878 with 3% mutation frequency and circulating tumor DNA (ctDNA of 1%, 3% and 5%) showed that the increase of sequencing depth reduced the fluctuation range of detected-VAFs around the expected VAFs, that is, the fidelity was improved. Finally, based on our experiment result, the consistency of single-nucleotide variants (SNVs) between paired FF and FFPE samples of mice increased with increasing depth, suggesting that increasing depth can improve the precision and sensitivity of low-frequency mutations. HighlightsThe normalized relationship between sequencing depth and the probability of true positive mutation (sensitivity) is established based on binomial distribution. The probability of true positive increases and the probability of false positive decreases when the number of positive mutated reads increases (threshold) in an equal proportion with depth. Detected-VAFs fluctuates regularly around expected-VAFs. The amplitude of detected-VAFs fluctuation decreases with sequencing depth and the "fidelity" increases. The increase of "fidelity" leads to a higher degree of differentiation between true and false positive mutations, which ultimately increases the true positive probability and decreases the false positive probability.

genomics↗

bioRxiv2021

Molecular mechanisms governing circulating immune cell heterogeneity across different species revealed by single cell sequencing

BackgroundImmune cells play important roles in mediating immune response and host defense against invading pathogens. However, insights into the molecular mechanisms governing circulating immune cell diversity among multiple species are limited. MethodsIn this study, we compared the single-cell transcriptomes of 77{square}957 immune cells from 12 species using single-cell RNA-sequencing (scRNA-seq). Distinct molecular profiles were characterized for different immune cell types, including T cells, B cells, natural killer cells, monocytes, and dendritic cells. ResultsResults revealed the heterogeneity and compositions of circulating immune cells among 12 different species. Additionally, we explored the conserved and divergent cellular crosstalk and genetic regulatory networks among vertebrate immune cells. Notably, the ligand and receptor pair VIM-CD44 was highly conserved among the immune cells. ConclusionsThis study is the first to provide a comprehensive analysis of the cross-species single-cell atlas for peripheral blood mononuclear cells (PBMCs). This research should advance our understanding of the cellular taxonomy and fundamental functions of PBMCs, with important implications in evolutionary biology, developmental biology, and immune system disorders.

cell biology↗

bioRxiv2021

Volumetric Tomographic 3D Bioprinting of Heterocellular Bone-like Tissues in Seconds

Tomographic volumetric bioprinting (VBP) has recently emerged as a powerful tool for rapid solidification of cell-laden hydrogel constructs within seconds. However, its practical applications in tissue engineering requires a detailed understanding of how different printing parameters (concentration of resins, laser dose) affect cell activity and tissue formation. Herein, we explore a new application of VBP in bone tissue engineering by merging a soft gelatin methacryloyl (GelMA) bioresin (<5 kPa) with 3D endothelial co-culture to generate heterocellular bone-like constructs with enhanced functionality. To this, a series of bioresins with varying concentrations of GelMA and lithium Phenyl(2,4,6-trimethylbenzoyl)phosphinate (LAP) photoinitiator were formulated and characterized in terms of photo-reactivity, printability and cell-compatibility. A bioresin with 5% GelMA and 0.05% LAP was identified as the optimal formulation for VBP of complex perfusable constructs within 30 s at high cell viability (>90%). The fidelity was validated by micro-computed tomography and confocal microscopy. Compared to 10% GelMA, this bioresin provided a softer and more permissive environment for osteogenic differentiation of human mesenchymal stem cells (hMSCs). The expression of osteoblastic markers (collagen-I, ALP, osteocalcin) and osteocytic markers (podoplanin, Dmp1) was monitored for 42 days. After 21 days, early osteocytic markers were significantly increased in 3D co-cultures with human umbilical vein endothelial cells (HUVECs). Additionally, we demonstrate VBP of a perfusable, pre-vascularized model where HUVECs self-organized into an endothelium-lined channel. Altogether, this work leverages the benefits of VBP and 3D co-culture, offering a promising platform for fast scaled biofabrication of 3D bone-like tissues with unprecedented functionality. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/468504v4_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1294740org.highwire.dtl.DTLVardef@104d811org.highwire.dtl.DTLVardef@105677dorg.highwire.dtl.DTLVardef@1cd60e4_HPS_FORMAT_FIGEXP M_FIG C_FIG Statement of significanceThis study explores new strategies for ultrafast bio-manufacturing of bone tissue models by leveraging the advantages of tomographic volumetric bioprinting (VBP) and endothelial co-culture. After screening the properties of a series of photocurable gelatin methacryloyl (GelMA) bioresins, a formulation with 5% GelMA was identified with optimal printability and permissiveness for osteogenic differentiation of human mesenchymal stem cells (hMSC). We then established 3D endothelial co-cultures to test if the heterocellular interactions may enhance the osteogenic differentiation in the printed environments. This hypothesis was evidenced by increased gene expression of early osteocytic markers in 3D co-cultures after 21 days. Finally, VBP of a perfusable cell-laden tissue construct is demonstrated for future applications in vascularized tissue engineering.

bioengineering↗

bioRxiv2021

Following the Trail of One Million Genomes: Footprints of SARS-CoV-2 Adaptation to Humans

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has accumulated genomic mutations at an approximately linear rate since it first infected human populations in late 2019. Controversies remain regarding the identity, proportion, and effects of adaptive mutations as SARS-CoV-2 evolves from a bat-to a human-adapted virus. The potential for vaccine-escape mutations poses additional challenges in pandemic control. Despite being of great interest to therapeutic and vaccine development, human-adaptive mutations in SARS-CoV-2 are masked by a genome-wide linkage disequilibrium under which neutral and even deleterious mutations can reach fixation by chance or through hitchhiking. Furthermore, genome-wide linkage equilibrium imposes clonal interference by which multiple adaptive mutations compete against one another. Informed by insights from microbial experimental evolution, we analyzed close to one million SARS-CoV-2 genomes sequenced during the first year of the COVID-19 pandemic and identified putative human-adaptive mutations according to the rates of synonymous and missense mutations, temporal linkage, and mutation recurrence. Furthermore, we developed a forward-evolution simulator with the realistic SARS-CoV-2 genome structure and base substitution probabilities able to predict viral genome diversity under neutral, background selection, and adaptive evolutionary models. We conclude that adaptive mutations have emerged early, rapidly, and constantly to dominate SARS-CoV-2 populations despite clonal interference and purifying selection. Our analysis underscores a need for genomic surveillance of mutation trajectories at the local level for early detection of adaptive and immune-escape variants. Putative human-adaptive mutations are over-represented in viral proteins interfering host immunity and binding host-cell receptors and thus may serve as priority targets for designing therapeutics and vaccines against human-adapted forms of SARS-CoV-2.

evolutionary biology↗

bioRxiv2021

A global multiregional proteomic map of the human cerebral cortex

The Brodmann area (BA)-based map is one of the most widely used cortical maps for studies of human brain functions and in clinical practice; however, the molecular architecture of BAs remain unknown. The present study provided a global multiregional proteomic map of the human cerebral cortex by analyzing 29 BAs. These 29 BAs were grouped into 6 clusters based on similarities in proteomic patterns: the motor and sensory cluster, vision cluster, auditory cluster and Brocas area, Wernickes area cluster, cingulate cortex cluster, and heterogeneous function cluster. We identified 474 cluster-specific and 134 BA-specific signature proteins whose functions are closely associated with specialized functions and disease vulnerability of the corresponding cluster or BA. The findings of the present study could provide explanations for the functional connections between the anterior cingulate cortex and sensorimotor cortex and for anxiety-related function in the sensorimotor cortex. The brain transcriptomic and proteomic comparison indicated that they both could reflect the function of cerebral cortex, but showed different characteristics. These proteomic data are publicly available at the Human Brain Proteome Atlas (www.brain-omics.com). Our results may enhance our understanding of the molecular basis of brain functions and provide an important resource to support human brain research.

neuroscience↗

bioRxiv2021

Postpartum corticosterone and fluoxetine shift the tryptophan-kynurenine pathway in dams

Perinatal depression (PND) affects 15% of mothers. Selective serotonin reuptake inhibitors (SSRIs) are currently the first-line of treatment for PND but are not always efficacious. Previously, we found significant reductions in plasma tryptophan concentrations and higher hippocampal proinflammatory cytokine, IL-1b levels, due to maternal SSRI treatment. Both inflammation and tryptophan-kynurenine metabolic pathway (TKP) are associated with SSRI efficacy in individuals with major depressive disorder (MDD). TKP is divided into neuroprotective and neurotoxic pathways. Higher metabolite concentrations of the neurotoxic pathway are associated with depression onset and implicated in SSRI efficacy. Metabolites in TKP were investigated in a rodent model of de novo postpartum depression (PPD) given treatment with the SSRI, fluoxetine (FLX). Dams were administered corticosterone (CORT) (40mg/kg, s.c.), and treated with the SSRI, fluoxetine (FLX) (10mg/kg, s.c.), during the postpartum for 22 days after parturition. Plasma TKP metabolite concentrations were quantified on the last day of treatment. Maternal postpartum CORT increased neurotoxic metabolites and co-enzyme/cofactors in dams (3-hydroxykynurenine, 3-hydroxyanthranilic acid, vitamin B2, flavin adenine dinucleotide). The combination of both CORT and FLX shifted the neuroprotective-to-neurotoxic ratio towards neurotoxicity. Postpartum FLX decreased plasma xanthurenic acid concentrations. Together, our data indicate higher neurotoxic TKP expression due to maternal postpartum CORT treatment, similar to clinical presentation of MDD. Moreover, maternal FLX treatment showed limited efficacy to influence TKP metabolites, which may correspond to its limited efficacy to treat depressive-like endophenotypes. Overall suggesting changes in TKP may be used as a biomarker of de novo PPD and antidepressant efficacy and targeting this pathway may serve as a potential therapeutic target. HighlightsO_LITryptophan-kynurenine pathway (TKP) is altered by postpartum corticosterone (CORT) C_LIO_LIPostpartum CORT upregulated neurotoxic more metabolites (3HK, 3HAA) C_LIO_LIPostpartum fluoxetine (FLX) increased xanthurenic acid concentrations C_LIO_LIPostpartum CORT and FLX together shifted the TKP balance towards neurotoxicity C_LI

neuroscience↗

bioRxiv2021

Brain transcriptional regulatory architecture and schizophrenia etiology converge between East Asian and European ancestral populations

Understanding the genetic architecture of gene expression and splicing in human brain is critical to unlocking the mechanisms of complex neuropsychiatric disorders like schizophrenia (SCZ). Large-scale brain transcriptomic studies are based primarily on populations of European (EUR) ancestry. The uniformity of mono-racial resources may limit important insights into the disease etiology. Here, we characterized brain transcriptional regulatory architecture of East Asians (EAS; n=151), identifying 3,278 expression quantitative trait loci (eQTL) and 4,726 spliceQTL (sQTL). Comparing these to PsychENCODE/BrainGVEX confirmed our hypothesis that the transcriptional regulatory architecture in EAS and EUR brains align. Furthermore, distinctive allelic frequency and linkage disequilibrium impede QTL translation and gene-expression prediction accuracy. Integration of eQTL/sQTL with genome-wide association studies reveals common and novel SCZ risk genes. Pathway-based analyses showing shared SCZ biology point to synaptic and GTPase dysfunction as a prospective pathogenesis. This study elucidates the transcriptional landscape of the EAS brain and emphasizes an essential convergence between EAS and EUR populations.

genetics↗

bioRxiv2020

Maximum Antigen Diversification in a Lyme Bacterial Population and Evolutionary Strategies to Overcome Pathogen Diversity

Natural populations of microbes and their hosts are engaged in an arms race in which microbes diversify to escape host immunity while hosts evolve novel immunity. This co-evolutionary process, known as the "Red Queen" hypothesis, poses a fundamental challenge to the development of broadly effective vaccines and diagnostics against a diversifying pathogen. Based on surveys of natural allele frequencies and experimental immunization of mice, we show minimal antigenic cross-reactivity among natural variants of the outer surface protein C (OspC), a dominant antigen of a Lyme Disease-causing bacterium (Borrelia burgdorferi). To overcome the challenge of OspC antigenic diversity to clinical development of preventive measures, we implemented a number of evolution-based strategies to broaden OspC immunological cross-reactivity. In particular, the centroid algorithm - a genetic algorithm to minimize sequence differences with natural variants - generated synthetic OspC analogs with the greatest promise as diagnostic and vaccine candidates against diverse Lyme pathogen strains coexisting in the Northeast United States. Mechanistically, we propose a model of runaway maximum antigen di-versification (MAD) mediated by amino-acid variations distributed across hypervariable regions on the OspC molecule. Under the MAD model, evolutionary centroids display high cross-reactivity by occupying the central void in the antigenic space excavated by diversifying natural variants. In contrast to the vaccine design based on concatenated epitopes, the centroid algorithm generates analogs of native antigens and is automated. The MAD model and evolution-inspired antigen designs have broad implications for combating diversifying pathogens driven by pathogen-host coevolution. ImportanceMicrobial pathogens rely on molecular diversity of cell surface antigens to escape host immunity. Vaccines based on one antigen variant often fail to protect the host against pathogens carrying other variants. Here we show evolution-based designs of synthetic antigens that are broadly reactive to all natural variants. The evolutionary analogs of a major surface antigen of a Lyme disease bacterium (Borrelia burgdorferi) showed promise as vaccine candidates against diverse pathogen strains coexisting in the endemic areas of Lyme disease in Northeast United States. Our evolution-based computational design is automated, generates molecular analogs of natural antigens, and opens a novel path to combating fast-evolving microbial pathogens.

microbiology↗

bioRxiv2020

powerEQTL: An R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis

SummaryGenome-wide association studies (GWAS) have revealed thousands of genetic loci for common diseases. One of the main challenges in the post-GWAS era is to understand the causality of the genetic variants. Expression quantitative trait locus (eQTL) analysis has been proven to be an effective way to address this question by examining the relationship between gene expression and genetic variation in a sufficiently powered cohort. However, it is often tricky to determine the sample size at which a variant with a specific allele frequency will be detected to associate with gene expression with sufficient power. This is particularly demanding with single-cell RNAseq studies. Therefore, a user-friendly tool to perform power analysis for eQTL at both bulk tissue and single-cell level will be critical. Here, we presented an R package called powerEQTL with flexible functions to calculate power, minimal sample size, or detectable minor allele frequency in both bulk tissue and single-cell eQTL analysis. A user-friendly, program-free web application is also provided, allowing customers to calculate and visualize the parameters interactively. Availability and implementationThe powerEQTL R package source code and online tutorial are freely available at CRAN: https://cran.r-project.org/web/packages/powerEQTL/. The R shiny application is publicly hosted at https://bwhbioinfo.shinyapps.io/powerEQTL/. ContactXianjun Dong (xdong@rics.bwh.harvard.edu), Weiliang Qiu (weiliang.qiu@sanofi.com) Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2020

IOBR: Multi-omics Immuno-Oncology Biological Research to decode tumor microenvironment and signatures

MotivationRecent advance in next generation sequencing has triggered the rapid accumulation of publicly available multi-omics datasets. The application of integrated omics to exploring robust signatures for clinical translation is increasingly highlighted, attributed to the clinical success of immune checkpoint blockade in diverse malignancies. However, effective tools to comprehensively interpret multi-omics data is still warranted to provide increased granularity into intrinsic mechanism of oncogenesis and immunotherapeutic sensitivity. ResultsWe developed a computational tool for effective Immuno-Oncology Biological Research (IOBR), providing comprehensive investigation of estimation of reported or user-built signatures, TME deconvolution and signature construction base on multi-omics data. Notably, IOBR offers batch analyses of these signatures and their correlations with clinical phenotypes, lncRNA profiling, genomic characteristics and signatures generated from single-cell RNA sequencing data in different cancer settings. Additionally, IOBR also integrates multiple existing microenvironmental deconvolution methodologies and signature construction tools for convenient comparison and selection. Collectively, IOBR is a user-friendly tool, to leverage multi-omics data to facilitate immuno-oncology exploration and unveiling of tumor-immune interactions and accelerating precision immunotherapy.

bioinformatics↗

bioRxiv2020

SPDE: A Multi-functional Software for Sequence Processing and Data Extraction

Efficiently extracting information from biological big data can be a huge challenge for people (especially those who lack programming skills). We developed Sequence Processing and Data Extraction (SPDE) as an integrated tool for sequence processing and data extraction for gene family and omics analyses. Currently, SPDE has seven modules comprising 100 basic functions that range from single gene processing (e.g., translation, reverse complement, and primer design) to genome information extraction. All SPDE functions can be used without the need for programming or command lines. The SPDE interface has enough prompt information to help users run SPDE without barriers. In addition to its own functions, SPDE also incorporates the publicly available analyses tools (such as, NCBI-blast, HMMER, Primer3 and SAMtools), thereby making SPDE a comprehensive bioinformatics platform for big biological data analysis. AvailabilitySPDE was built using Python and can be run on 32-bit, 64-bit Windows and macOS systems. It is an open-source software that can be downloaded from https://github.com/simon19891216/SPDEv1.2.git. Contactxudongzhuanyong@163.com

bioinformatics↗

bioRxiv2020

MicroRNA variants and HLA-miRNA interactions are novel rheumatoid arthritis susceptibility factors

ObjectiveAlthogh Genome-wide association studies have identified >100 variants for rheumatoid arthritis (RA),the reported genetic variants only explain <40% of RA heritability. We conducted a systemic association study between common East-Asian miRNA SNPs with RA in a large Han Chinese cohort to explain missing heritability and identify miRNA epistatic interactions. Methods4 HLA SNPs (HLA-DRB1, HLA-DRB9, HLA-DQB1 and TNFAIP3) and 225 common SNPs located in miRNA which might influence the miRNA target binding or pre-miRNA stability were genotyped in 1,607 rheumatoid arthritis and 1,580 matched normal individuals. A meta-analysis with previous GWAS studies (4,873 RA cases and 17,642 controls) was performed to discovery another novel miRNA RA-associated SNPs. Results2 novel SNPs including rs1414273 (miR-548ac, OR=0.84, P=8.26x10-4) and rs2620381 (miR-627, OR=0.77, P=2.55x10-3) conferred significant association with RA. Individuals carried 8 risk alleles showed 15.38 (95%CI: 4.69-50.49, P<1.0x10-6) times more risk to be affected by RA. In addition, rs5997893 (miR-3928) showed significant epistasis effect with rs4947332 (HLA-DRB1, OR=4.23, P=0.04) and rs2967897 (miR-5695) with rs7752903 (TNFAIP3, OR=4.43, P=0.03). Finally, we demonstrated targets of the significant miRNAs showed enrichment in immune related genes (P=2.0x10-5) and FDA approved drug target genes (P=0.014). Conclusions6 novel miRNA SNPs including rs1414273 (miR-548ac, P=8.26x10-4), rs2620381 (miR-627, P=2.55x10-3), rs4285314 (miR-3135b, P=1.10x10-13), rs28477407 (miR-4308, P=3.44x10-5), rs5997893 (miR-3928, P=5.9x10-3) and rs45596840 (miR-4482, P=6.6x10-3) were confirmed to be significantly associated with RA in a Chinese population. Our study suggests that miRNAs might be interesting targets to accelerate the understanding of the pathogenesis and drug development for rheumatoid arthritis.

genetics↗

bioRxiv2020

Robust Benchmark Structural Variant Calls of An Asian Using the State-of-Art Long Fragment Sequencing Technologies

The importance of structural variants (SVs) on phenotypes and human diseases is now recognized. Although a variety of SV detection platforms and strategies that vary in sensitivity and specificity have been developed, few benchmarking procedures are available to confidently assess their performances in biological and clinical research. To facilitate the validation and application of those approaches, our work established an Asian reference material comprising identified benchmark regions and high-confidence SV calls. We established a high-confidence SV callset with 8,938 SVs in an EBV immortalized B lymphocyte line, by integrating four alignment-based SV callers [from 109x PacBio continuous long read (CLR), 22x PacBio circular consensus sequencing (CCS) reads, 104x Oxford Nanopore long reads, and 114x optical mapping platform (Bionano)] and one de novo assembly-based SV caller using CCS reads. A total of 544 randomly selected SVs were validated by PCR and Sanger sequencing, proofing the robustness of our SV calls. Combining trio-binning based haplotype assemblies, we established an SV benchmark for identification of false negatives and false positives by constructing the continuous high confident regions (CHCRs), which cover 1.46Gb and 6,882 SVs supported by at least one diploid haplotype assembly. Establishing high-confidence SV calls for a benchmark sample that has been characterized by multiple technologies provides a valuable resource for investigating SVs in human biology, disease, and clinical diagnosis.

genomics↗

bioRxiv2020

Single-cell screening of SARS-CoV-2 target cells in pets, livestock, poultry and wildlife

A few animals have been suspected to be intermediate hosts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, a large-scale single-cell screening of SARS-CoV-2 target cells on a wide variety of animals is missing. Here, we constructed the single-cell atlas for 11 representative species in pets, livestock, poultry, and wildlife. Notably, the proportion of SARS-CoV-2 target cells in cat was found considerably higher than other species we investigated and SARS-CoV-2 target cells were detected in multiple cell types of domestic pig, implying the necessity to carefully evaluate the risk of cats during the current COVID-19 pandemic and keep pigs under surveillance for the possibility of becoming intermediate hosts in future coronavirus outbreak. Furthermore, we screened the expression patterns of receptors for 144 viruses, resulting in a comprehensive atlas of virus target cells. Taken together, our work provides a novel and fundamental strategy to screen virus target cells and susceptible species, based on single-cell transcriptomes we generated for domesticated animals and wildlife, which could function as a valuable resource for controlling current pandemics and serve as an early warning system for coping with future infectious disease threats.

cell biology↗